Title
Detection and severity of tumor cells by graded decision-making methods under fuzzy -soft model.
Abstract
The notion of fuzzy N-soft sets is a hybrid model, which is a more generalized framework than fuzzy soft sets. To investigate the objects of a reference set in medical field, which have uncertainties in data, can be correctly captured by proposed structures of novel decision-making methods, graded TOPSIS and graded ELECTRE-I methods, based on fuzzy N-soft sets (henceforth, (F, N)-soft sets). Both the proposed methods compute the decision-maker estimations in a more flexile and affluent way, as well as improve the reliability of the decisions, that depends on star ratings or grades for the purpose of the modelization of decision-making problems in medical field. We show the importance and feasibility of proposed methods by applying them on real life example in medical field having ambiguities, that can be accurately occupied by this framework. Finally, we discuss the comparison analysis of both the proposed decision-making methods.
Year
DOI
Venue
2020
10.3233/JIFS-192203
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Keywords
DocType
Volume
N-soft sets,(F, N)-soft sets,graded TOPSIS,graded ELECTRE-I,decision-making
Journal
39
Issue
ISSN
Citations 
1
1064-1246
1
PageRank 
References 
Authors
0.35
0
4
Name
Order
Citations
PageRank
Arooj Adeel192.15
Muhammad Akram236554.94
Naveed Yaqoob342.41
Wathek Chammam443.09